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Performance evaluation of road detection and following algorithms



Tsai H. Hong, A Takeuchi, M Foedissch, Michael O. Shneier


We describe a methodology for evaluating algorithms to provide quantitative information about how well road detection and road following algorithms perform. The approach relies on generating a set of standard data sets annotated with ground truth. We evaluate the algorithms used to detect roads by comparing the output of the algorithms with ground truth, which we obtain by having humans annotate the data sets used to test the algorithms. Ground truth annotations are acquired from more than one person to reduce systematic errors. Results are quantified by looking at false positive and false negative regions of the image sequences when compared with the ground truth. We describe the evaluation of a number of variants of a road detection system based on neural networks.
Proceedings Title
Proceedings of SPIE Optics East 2004
Conference Dates
October 25-28, 2004
Conference Location
Philadelphia, PA, USA
Conference Title
Industrial Optical Robotic Systems Technology & Applications


false negative, false positive, groud truth, Mobility, performance evaluation, Performance Metrics, road detection, Robotics & Intelligent Systems, Vision


Hong, T. , Takeuchi, A. , Foedissch, M. and Shneier, M. (2004), Performance evaluation of road detection and following algorithms, Proceedings of SPIE Optics East 2004, Philadelphia, PA, USA, [online], (Accessed June 20, 2024)


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Created October 27, 2004, Updated October 12, 2021